Highly selective chemical and biological sensors

ABSTRACT

Methods and sensors for selective fluid sensing are provided. A sensor includes a resonant inductor-capacitor-resistor (LCR) circuit and a sensing material disposed over the LCR circuit. The sensing material includes a coordination compound of a ligand and a metal nanoparticle. The coordination compound has the formula: (X)n-M, where X includes an alkylamine group having the formula (R—NH2), an alkylphosphine having the formula (R3—P), an alkylphosphine oxide having the formula (R3P═O), an alkyldithiocarbamate having the formula (R2NCS2), an alkylxanthate having the formula (ROCS2), or any combination thereof, R includes an alkyl group, n is 1, 2, or 3, and M includes the metal nanoparticle of gold, silver, platinum, palladium, alloys thereof, highly conductive metal nanoparticles, or any combination thereof. The sensing material is configured to allow selective detection of at least six different analyte fluids from an analyzed fluid mixture.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a Divisional of application Ser. No. 15/794,815entitled “Highly Selective Chemical and Biological Sensors,” filed Oct.26, 2017, which is a Divisional of U.S. application Ser. No. 12/977,568entitled “Highly Selective Chemical and Biological Sensors,” filed Dec.23, 2010, and now abandoned, which is hereby incorporated by referencein its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH & DEVELOPMENT

This invention was made with Government support and funded in part bythe National Institute of Environmental Health Sciences under Grant No.1R01ES016569-01A1. The Government has certain rights in the invention.

BACKGROUND

The subject matter disclosed herein relates to chemical and biologicalsensors, and more particularly, to highly selective chemical andbiological sensors.

Chemical and biological sensors are often employed in a number ofapplications where the detection of various vapors may be used todiscern useful information. For instance, measuring the presence ofvapors by discerning a change in certain environmental variables withinor surrounding a sensor may be particularly useful in monitoring changesin biopharmaceutical products, food or beverages, monitoring industrialareas for chemical or physical hazards, as well as in securityapplications, such as residential home monitoring, home land security inairports, in different environmental and clinical settings, and otherpublic venues wherein detection of certain harmful and/or toxic vaporsmay be particularly useful.

One technique for sensing such environmental changes is by employing asensor, such as an RFID sensor, coated with a particular sensingmaterial. In addition, sensors may be arranged in an array of individualtransducers, which are coated with one or more sensing materials. Manysensor arrays include a number of identical sensors. However, whileusing identical sensors simplifies fabrication of the sensor array, suchan array may have limited capabilities for sensing only a singleresponse (e.g. resistance, current, capacitance, work function, mass,optical thickness, light intensity, etc). In certain applicationsmultiple responses or changes in multiple properties may occur. In suchapplications, it may be beneficial to include an array of sensorswherein different transducers in the array employ the same or differentresponses (e.g. resistance, current, capacitance, work function, mass,optical thickness, light intensity, etc.) and are coated with differentsensing materials such that more than one property can be measured.Disadvantageously, fabricating a sensor array having individual sensorsuniquely fabricated to sense a particular response, complicatesfabrication of the array.

Further, in many practical applications, it is beneficial to use highlyselective chemical and biological sensors. That is, it is oftendesirable to provide a sensor array capable of sensing multiple vaporsand vapor mixtures in the presence of other vapors and mixtures. Thegreater the number of vapors and vapor mixtures that may be present, themore difficult it may be to accurately sense and discern a specific typeof vapor or vapor mixture being sensed. This may be particularly truewhen one or more vapors are present at levels of magnitude greater thanthe other vapors of interest for detection. For instance, high humidityenvironments often interfere with the ability of traditional sensors todetect selected vapors.

Various embodiments disclosed herein may address one or more of thechallenges set forth above.

BRIEF DESCRIPTION

In accordance with one embodiment, there is provided a sensor thatincludes a resonant inductor-capacitor-resistor (LCR) circuit and asensing material disposed over the LCR circuit. The sensing materialincludes a coordination compound of a ligand and a metal nanoparticle.The coordination compound has the formula: (X)_(n)-M, where X includesan alkylamine group having the formula (R—NH₂), an alkylphosphine havingthe formula (R₃—P), an alkylphosphine oxide having the formula (R₃P═O),an alkyldithiocarbamate having the formula (R₂NCS₂), an alkylxanthatehaving the formula (ROCS₂), or any combination thereof, R includes analkyl group, n is 1, 2, or 3, and M includes the metal nanoparticle ofgold, silver, platinum, palladium, alloys thereof, highly conductivemetal nanoparticles, or any combination thereof. The sensing material isconfigured to allow selective detection of at least six differentanalyte fluids from an analyzed fluid mixture.

In accordance with another embodiment, there is provided a method ofdetecting chemical or biological species in a fluid. The method includesmeasuring a real part and an imaginary part of an impedance spectrum ofa resonant sensor antenna coated with a coordination compound of aligand and a metal nanoparticle. The ligand includes a primary alkylamine, trialkylphosphine, trialkylphosphine oxide, alkyldithiocarbamate,alkylxanthate or any combination thereof. The method further includescalculating at least six spectral parameters of the resonant sensorantenna coated with the coordination compound. The method furtherincludes reducing the impedance spectrum to a single data point usingmultivariate analysis to selectively identify an analyte. The methodfurther includes determining one or more environmental parameters fromthe impedance spectrum.

In accordance with another embodiment, there is provided a sensor thatincludes a transducer and a coordination compound of a ligand and ametal nanoparticle disposed on the transducer. The transducer has amultivariate output to independently detect effects of differentenvironmental parameters on the sensor. The coordination compound has apreserved magnitude of response to an analyte over a broad concentrationrange of an interferent. In addition, the coordination compound has theformula: (X)_(n)-M, where X includes an alkylamine group having theformula (R—NH₂), an alkylphosphine having the formula (R₃—P), analkylphosphine oxide having the formula (R₃P═O), an alkyldithiocarbamatehaving the formula (R₂NCS₂), an alkylxanthate having the formula(ROCS₂), or any combination thereof, R includes an alkyl group, n is 1,2, or 3, and M includes the metal nanoparticle of gold, silver,platinum, palladium, alloys thereof, highly conductive metalnanoparticles, or any combination thereof.

DRAWINGS

These and other features, aspects, and advantages of the presentinvention will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 illustrates a sensing system, in accordance with embodiments ofthe invention;

FIG. 2 illustrates an RFID sensor, in accordance with embodiments of theinvention;

FIG. 3 illustrates an RFID sensor, in accordance with alternateembodiments of the invention;

FIG. 4 illustrates measured responses of an RFID sensor, in accordancewith embodiments of the invention;

FIG. 5 illustrates a sensing material, in accordance with embodiments ofthe invention; and

FIGS. 6 and 7 illustrate test data demonstrating a single sensor capableof discriminating between water vapor and nine individual alcohol vaporsfrom their homologous series, in accordance with embodiments of theinvention.

DETAILED DESCRIPTION

Embodiments disclosed herein provide methods and systems for selectivevapor sensing wherein a single sensor is provided and is capable ofdetecting multiple vapors and/or mixtures of vapors alone, or in thepresence of one another. Examples of such methods and sensors aredescribed in U.S. patent application Ser. No. 12/942,732 entitled“Highly Selective Chemical and Biological Sensors,” which isincorporated herein by reference. The disclosed sensors are capable ofdetecting different vapors and mixtures even in a high humidityenvironment or an environment wherein one or more vapors has asubstantially higher concentration (e.g. 10 x) compared to othercomponents in the mixture. Each sensor includes a resonantinductor-capacitor-resistor (LCR) sensor that is coated with a sensingmaterial, namely a coordination compound of a primary alkyl amine and ametal nanoparticle, as further described below. Sensing materials thatinclude exemplary coordination compounds may provide improved abilityfor selective vapor sensing and improved stability of response comparedto the performance of other sensing materials, such as sensing materialsthat include thiol groups. Non-limiting examples of LCR sensors includeRFID sensors with an integrated circuit (IC) memory chip, RFID sensorswith an IC chip, and RFID sensors without an IC memory chip (chiplessRFID sensors). LCR sensors can be wireless or wired. In order to collectdata, an impedance spectrum is acquired over a relatively narrowfrequency range, such as the resonant frequency range of the LCRcircuit. The technique further includes calculating the multivariatesignature from the acquired spectrum and manipulating the data todiscern the presence of certain vapors and/or vapor mixtures. Thepresence of vapors is detected by measuring the changes in dielectric,dimensional, charge transfer, and other changes in the properties of thematerials employed by observing the changes in the resonant electronicproperties of the circuit. By using a mathematical procedure, such asprincipal component analysis (PCA) and others, multiple vapors andmixtures can be detected in the presence of one another and in thepresence of an interferent as further described below. Embodimentsdisclosed herein provide methods and systems for selective fluid sensingwherein a single sensor is provided and is capable of detecting multiplefluids and/or mixtures of fluids alone, or in the presence of oneanother.

To more clearly and concisely describe the subject matter of the claimedinvention, the following definitions are provided for specific terms,which are used in the following description and the appended claims.

The term “fluids” includes gases, vapors, liquids, and solids.

The term “digital ID” includes all data stored in a memory chip of theRFID sensor. Non-limiting examples of this data are manufactureridentification, electronic pedigree data, user data, and calibrationdata for the sensor.

The term “monitoring process” includes, but is not limited to, measuringphysical changes that occur around the sensor. For example, monitoringprocesses including monitoring changes in a biopharmaceutical, food orbeverage manufacturing process related to changes in physical, chemical,and/or biological properties of an environment around the sensor.Monitoring processes may also include those industry processes thatmonitor physical changes as well as changes in a component's compositionor position. Non-limiting examples include homeland security monitoring,residential home protection monitoring, environmental monitoring,clinical or bedside patient monitoring, airport security monitoring,admission ticketing, and other public events. Monitoring can beperformed when the sensor signal has reached an appreciably steady stateresponse and/or when the sensor has a dynamic response. The steady statesensor response is a response from the sensor over a determined periodof time, where the response does not appreciably change over themeasurement time. Thus, measurements of steady state sensor responseover time produce similar values. The dynamic sensor response is aresponse from the sensor upon a change in the measured environmentalparameter (temperature, pressure, chemical concentration, biologicalconcentration, etc.). Thus, the dynamic sensor response significantlychanges over the measurement time to produce a dynamic signature ofresponse toward the environmental parameter or parameters measured.Non-limiting examples of the dynamic signature of the response includeaverage response slope, average response magnitude, largest positiveslope of signal response, largest negative slope of signal response,average change in signal response, maximum positive change in signalresponse, and maximum negative change in signal response. The produceddynamic signature of response can be used to further enhance theselectivity of the sensor in dynamic measurements of individual vaporsand their mixtures. The produced dynamic signature of response can alsobe used to further optimize the combination of sensing material andtransducer geometry to enhance the selectivity of the sensor in dynamicand steady state measurements of individual vapors and their mixtures.

The term “environmental parameters” is used to refer to measurableenvironmental variables within or surrounding a manufacturing ormonitoring system. The measurable environmental variables comprise atleast one of physical, chemical, and biological properties and include,but are not limited to, measurement of temperature, pressure, materialconcentration, conductivity, dielectric property, number of dielectric,metallic, chemical, or biological particles in the proximity or incontact with the sensor, dose of ionizing radiation, and lightintensity.

The term “analyte” includes any desired measured environmentalparameter.

The term “interference” includes any undesired environmental parameterthat undesirably affects the accuracy and precision of measurements withthe sensor. The term “interferent” refers to a fluid or an environmentalparameter (that includes, but is not limited to temperature, pressure,light, etc.) that potentially may produce an interference response bythe sensor.

The term “multivariate analysis” refers to a mathematical procedure thatis used to analyze more than one variable from the sensor response andto provide the information about the type of at least one environmentalparameter from the measured sensor spectral parameters and/or toquantitative information about the level of at least one environmentalparameter from the measured sensor spectral parameters. The term“principal components analysis (PCA)” refers to a mathematical procedurethat is used to reduce multidimensional data sets to lower dimensionsfor analysis. Principal component analysis is a part of eigenanalysismethods of statistical analysis of multivariate data and may beperformed using a covariance matrix or correlation matrix. Non-limitingexamples of multivariate analysis tools include canonical correlationanalysis, regression analysis, nonlinear regression analysis, principalcomponents analysis, discriminate function analysis, multidimensionalscaling, linear discriminate analysis, logistic regression, or neuralnetwork analysis.

The term “spectral parameters” is used to refer to measurable variablesof the sensor response. The sensor response is the impedance spectrum ofthe resonance sensor circuit of the LCR or RFID sensor. In addition tomeasuring the impedance spectrum in the form of Z-parameters,S-parameters, and other parameters, the impedance spectrum (its bothreal and imaginary parts) may be analyzed simultaneously using variousparameters for analysis, such as, the frequency of the maximum of thereal part of the impedance (F_(p)), the magnitude of the real part ofthe impedance (Z_(p)), the resonant frequency of the imaginary part ofthe impedance (F₁), and the anti-resonant frequency of the imaginarypart of the impedance (F₂), signal magnitude (Z₁) at the resonantfrequency of the imaginary part of the impedance (F₁), signal magnitude(Z₂) at the anti-resonant frequency of the imaginary part of theimpedance (F₂), and zero-reactance frequency (F_(z), frequency at whichthe imaginary portion of impedance is zero). Other spectral parametersmay be simultaneously measured using the entire impedance spectra, forexample, quality factor of resonance, phase angle, and magnitude ofimpedance. Collectively, “spectral parameters” calculated from theimpedance spectra, are called here “features” or “descriptors.” Theappropriate selection of features is performed from all potentialfeatures that can be calculated from spectra. Multivariable spectralparameters are described in U.S. patent application Ser. No. 12/118,950entitled “Methods and systems for calibration of RFID sensors,” which isincorporated herein by reference.

The term “resonance impedance” or “impedance” refers to measured sensorfrequency response around the resonance of the sensor from which thesensor “spectral parameters” are extracted.

The term “protecting material” includes, but is not limited to,materials on the LCR or RFID sensor that protect the sensor from anunintended mechanical, physical or chemical effect while stillpermitting the anticipated measurements to be performed. For example, ananticipated measurement may include solution conductivity measurementwherein a protecting film separates the sensor from the liquid solutionyet allows an electromagnetic field to penetrate into solution. Anexample of a protecting material is a paper film that is applied on topof the sensor to protect the sensor from mechanical damage and abrasion.Another non-limiting example of a protecting material is a polymer filmthat is applied on top of the sensor to protect the sensor fromcorrosion when placed in a liquid for measurements. A protectingmaterial may also be a polymer film that is applied on top of the sensorfor protection from shortening of the sensor's antenna circuit whenplaced in a conducting liquid for measurements. Non-limiting examples ofprotecting films are paper, polymeric, and inorganic films such aspolyesters, polypropylene, polyethylene, polyethers, polycarbonate,polyethylene terepthalate, zeolites, metal-organic frameworks, andcavitands. The protecting material can be arranged between thetransducer and sensing film to protect the transducer. The protectingmaterial can be arranged on top of the sensing film which is itself ison top of the transducer to protect the sensing film and transducer. Theprotecting material on top of the sensing film which is itself is on topof the transducer can serve to as a filter material to protect thesensing film from exposure to gaseous or ionic interferences.Non-limiting examples of filter materials include zeolites,metal-organic frameworks, and cavitands.

As used herein the term “sensing materials and sensing films” includes,but is not limited to, materials deposited onto a transducer'selectronics module, such as LCR circuit components or an RFID tag, toperform the function of predictably and reproducibly affecting theimpedance sensor response upon interaction with the environment. Inorder to prevent the material in the sensor film from leaching into theliquid environment, the sensing materials are attached to the sensorsurface using standard techniques, such as covalent bonding,electrostatic bonding, and other standard techniques known to those ofordinary skill in the art.

The terms “transducer and sensor” are used to refer to electronicdevices such as RFID devices intended for sensing. “Transducer” is adevice before it is coated with a sensing or protecting film or beforeit is calibrated for a sensing application. “Sensor” is a devicetypically after it is coated with a sensing or protecting film and afterbeing calibrated for the sensing application.

As used herein the term “RFID tag” refers to an identification andreporting technology that uses electronic tags for identifying and/ortracking articles to which the RFID tag may be attached. An RFID tagtypically includes at least two components where the first component isan integrated circuit (IC) memory chip for storing and processinginformation and modulating and demodulating a radio frequency signal.This memory chip can also be used for other specialized functions, forexample, it can contain a capacitor. It can also contain at least oneinput for an analog signal such as resistance input, capacitance input,or inductance input. In the case of a chipless RFID tag, the RFID tagmay not include an IC memory chip. This type of RFID tag may be usefulin applications where a specific RFID tag does not need to beidentified, but rather a signal merely indicating the presence of thetag provides useful information (e.g., product security applications).The second component of the RFID tag is an antenna for receiving andtransmitting the radio frequency signal.

The term “RFID sensor” is an RFID tag with an added sensing function as,for example, when an antenna of the RFID tag also performs sensingfunctions by changing its impedance parameters as a function ofenvironmental changes. The accurate determinations of environmentalchanges with such RFID sensors are performed by analysis of resonanceimpedance. For example, RFID tags may be converted into RFID sensors bycoating the RFID tag with a sensing film. By coating the RFID tag with asensing film, the electrical response of the film is translated intosimultaneous changes to the impedance response, resonance peak position,peak width, peak height and peak symmetry of the impedance response ofthe sensor antenna, magnitude of the real part of the impedance,resonant frequency of the imaginary part of the impedance, anti-resonantfrequency of the imaginary part of the impedance, zero-reactancefrequency, phase angle, and magnitude of impedance, and others asdescribed in the definition of the term sensor “spectral parameters.”The “RFID sensor” can have an integrated circuit (IC) memory chipattached to the antenna or can have no IC memory chip. An RFID sensorwithout an IC memory chip is an LCR sensor. An LCR sensor is comprisedof known components, such as at least one inductor (L), at least onecapacitor (C), and at least one resistor (R) to form an LCR circuit.

The term “single-use container” includes, but is not limited to,manufacturing or monitoring equipment, and packaging, which may bedisposed of after use or reconditioned for reuse. Single-use packagingin the food industry includes, but is not limited to, food and drinkspackaging, and candy and confection boxes. Single-use monitoringcomponents include, but are not limited to, single-use cartridges,dosimeters, and collectors. Single use manufacturing containers include,but are not limited to, single-use vessels, bags, chambers, tubing,connectors, and columns.

The term “writer/reader” includes, but is not limited to, a combinationof devices to write and read data into the memory of the memory chip andto read impedance of the antenna. Another term for “writer/reader” is“interrogator.”

In accordance with embodiments disclosed herein, an LCR or an RFIDsensor for sensing vapors, vapor mixtures, and biological species isdescribed. As previously described, the RFID sensor includes an RFID tagcoated with the coordination compound of a primary alkyl amine and ametal nanoparticle. In one embodiment, a passive RFID tag may beemployed. As will be appreciated, an RFID tag may include an IC memorychip, which is connected to an antenna coil for communication with awriter/reader. The IC memory chip can be read by illuminating the tag bya radio frequency (RF) and/or microwave carrier signal sent by thewriter/reader. When the RF and/or microwave field passes through theantenna coil, an AC voltage is generated across the coil. The voltage isrectified in the microchip to result in a DC voltage for the microchipoperation. The IC memory chip becomes functional when the DC voltagereaches a predetermined level. By detecting the RF and/or microwavesignal backscattered from the microchip, the information stored in themicrochip can be fully identified. The distance between the RFIDtag/sensor and the writer/reader is governed by the design parametersthat include operating frequency, RF and/or microwave power level, thereceiving sensitivity of the reader/writer, antenna dimensions, datarate, communication protocol, and microchip power requirements. Thedistance between the “RFID sensor” without an IC memory chip (chiplessRFID sensor or LCR sensor or LCR transducer) and the sensor reader isgoverned by the design parameters that include operating frequency, RFor microwave power level, the receiving sensitivity of the sensorreader, and antenna dimensions.

In one embodiment a passive RFID tag with or without an IC memory chipmay be employed. Advantageously, a passive RFID tag does not rely on abattery for operation. However, the communication distance between thewriter/reader and RFID tag is typically limited within a proximitydistance because the passive tag operates with only microwatts of RFpower from the writer/reader. For passive tags operating at 13.56 MHz,the read distance is typically not more than several centimeters. Thetypical frequency range of operation of 13.56 MHz passive RFID tags fordigital ID writing/reading is from 13.553 to 13.567 MHz. The typicalfrequency range of operation of 13.56-MHz passive RFID sensors forsensing of environmental changes around the RFID sensor is from about 5MHz to about 20 MHz, more preferably from 10 to 15 MHz. The requirementfor this frequency range is to be able to recognize the tag with awriter/reader that operates at 13.56 MHz while the sensor portion of theRFID tag operates from 5 to 20 MHz.

Depositing sensing films onto passive RFID tags creates RFID chemical orbiological sensors. RFID sensing is performed by measuring changes inthe RFID sensor's impedance as a function of environmental changesaround the sensor, as described further below. If the frequency responseof the antenna coil, after deposition of the sensing film, does notexceed the frequency range of operation of the tag, the informationstored in the microchip can be identified with a conventional RFIDwriter/reader. An impedance or network analyzer (sensor reader) can readthe impedance of the antenna coil to correlate the changes in impedanceto the chemical and biological species of interest and to physical,chemical, or/and biological changes of environmental parameters aroundthe sensor.

In operation, after coating of the RFID tag with a chemically sensitivefilm, both the digital tag ID and the impedance of the tag antenna maybe measured. The measured digital ID provides information about theidentity of the tag itself, such as an object onto which this tag isattached, and the properties of the sensor (e.g. calibration curves fordifferent conditions, manufacturing parameters, expiration date, etc.).For multi-component detection, multiple properties from the measuredreal and imaginary portions of the impedance of a single RFID sensor maybe determined, as described further below.

In summary, and in accordance with the embodiments described herein, inorder to achieve high selectivity detection of analytes in the presenceof high levels of interferences, the sensor should exhibit a number ofcharacteristics. First, the selected transducer should include amultivariate output to independently detect the effects of differentenvironmental parameters on the sensor. Second, the sensing materialshould have a preserved magnitude of response to an analyte over a wideconcentration range of an interferent. The response to the relativelysmall analyte concentrations should not be fully suppressed by thepresence of the relatively high concentrations of the interferents.Third, the response of the sensing material to interference species isallowed and may exist but should not compete with the response to theanalyte and should be in a different direction of the multivariateoutput response of the transducer.

To achieve these characteristics, in one embodiment, the sensingmaterial has multiple response mechanisms to vapors where these responsemechanisms are related to the changes of dielectric constant,resistance, and swelling of the sensing material where these changes arenot fully correlated with each other and produce different patterns uponexposure to individual vapors and their mixtures. Further, the LCRtransducer can have multiple components of LCR response from the LCRcircuit where these multiple components of LCR response originate fromthe different factors affecting the transducer circuit with thenon-limiting examples that include material resistance and capacitance,contact resistance and capacitance between the transducer and sensingmaterial, and resistance and capacitance between the transducersubstrate and sensing material. Further, the LCR transducer can havemultiple conditions of LCR circuit operation where an integrated circuitchip is a part of the sensor circuit.

Thus, one method for controlling the selectivity of the sensor responseinvolves powering of the integrated circuit chip to affect the impedancespectral profile. The different impedance spectral profiles change theselectivity of sensor response upon interactions with different vapors.The IC chip or IC memory chip on the resonant antenna contains arectifier diode and it can be powered at different power levels toinfluence the impedance spectral profile of the sensor. The differencesin spectral profiles at different power levels are pronounced indifferent values of F_(p), F₁, F₂, F_(z), Z_(p), Z₁, Z₂, and calculatedvalues of C and R. In one embodiment, the enhanced sensor selectivity isachieved through the appropriate selection of at least one power levelof the IC chip or IC memory chip operation. In another embodiment, theenhanced sensor selectivity is achieved through the appropriateselection of at least two power levels of the IC chip or IC memory chipoperation and analyzing the combined impedance spectral profiles of thesensor under different power levels. Powering of the sensor with atleast two power levels is performed in the alternating fashion between arelatively low and relatively high power. The alternating powering ofthe sensor with at least two power levels is performed on the time scalethat is at least 5 times faster than the dynamic changes in the measuredenvironmental parameters. In all these embodiments, powering atdifferent power levels is in the range from −50 dBm to +40 dBm andprovides the ability to detect more selectively more analytes and/or toreject more selectively more interferences.

Another method of controlling the selectivity of the sensor responseinvolves applying different powers to the LCR or to RFID sensor toaffect the dipole moment, the dielectric constant, and/or temperature ofthe material in proximity to the sensor. The material in proximity tothe sensor refers to the sensing material deposited onto the sensorand/or the fluid under investigation. These changes in the dipolemoment, the dielectric constant, and/or temperature of the material inproximity to the sensor when exposed to different power levels of LCR orRFID sensor operation originate from the interactions of theelectromagnetic field with these materials. Powering of the sensor withat least two power levels is performed in the alternating fashionbetween a relatively low and relatively high power. The alternatingpowering of the sensor with at least two power levels is performed onthe time scale that is at least 5 times faster than the dynamic changesin the measured environmental parameters. In all these embodiments,powering at different power levels is in the range from −50 dBm to +40dBm and provides the ability to detect more selectively more analytesand/or to reject more selectively more interferences.

Turning now to the figures and referring initially to FIG. 1, a sensingsystem 10 is provided to illustrate the principle of selective vaporsensing utilizing an RFID sensor 12 having a sensing material 14, namelythe coordination compound of a primary alkyl amine and a metalnanoparticle, coated thereon. Referring briefly to FIG. 2, the sensor 12is a resonant circuit that includes an inductor-capacitor-resistorstructure (LCR) coated with the sensing material 14. The sensingmaterial 14 is applied onto the sensing region between the electrodes,which form sensor antenna 18 that constitute the resonant circuit. Aswill be described further below, by applying the sensing material 14onto the resonant circuit, the impedance response of the circuit will bealtered. The sensor 12 may be a wired sensor or a wireless sensor. Thesensor 12 may also include a memory chip 16 coupled to resonant antenna18 that is coupled to a substrate 20. The memory chip 16 may includemanufacturing, user, calibration and/or other data stored thereon. Thememory chip 16 is an integrated circuit device and it includes RF signalmodulation circuitry fabricated using a complementary metal-oxidesemiconductor (CMOS) process and a non-volatile memory. The RF signalmodulation circuitry components include a diode rectifier, a powersupply voltage control, a modulator, a demodulator, a clock generator,and other components.

FIG. 3 illustrates an alternative embodiment of the sensor 12,designated by reference numeral 21, wherein a complementary sensor 23comprising the sensing material 14 is attached across the antenna 18 andthe integrated circuit (IC) memory chip 16 to alter the sensor impedanceresponse. In another embodiment (not illustrated), a complementarysensor may be attached across an antenna that does not have an IC memorychip and alters sensor impedance response. Non-limiting examples ofcomplementary sensors are interdigitated sensors, resistive sensors, andcapacitive sensors. Complementary sensors are described in U.S. patentapplication Ser. No. 12/118,950 entitled “Methods and systems forcalibration of RFID sensors,” which is incorporated herein by reference.

In one embodiment, a 13.56 MHz RFID tag may be employed. Duringoperation of the sensing system 10, the impedance Z(f) of the sensorantenna 18 and the digital sensor calibration parameters stored on thememory chip 16 may be acquired. Referring again to FIG. 1, measurementof the resonance impedance Z(f) of the antenna 18 and thereading/writing of digital data from the memory chip 16 are performedvia mutual inductance coupling between the RFID sensor antenna 18 andthe pickup coil 22 of a reader 24. As illustrated, the reader 24 mayinclude an RFID sensor impedance reader 26 and an integrated circuitmemory chip reader 28. The interaction between the RFID sensor 12 andthe pickup coil 22 can be described using a general mutual inductancecoupling circuit model. The model includes an intrinsic impedance Z_(C)of the pickup coil 22 and an intrinsic impedance Z_(S) of the sensor 12.The mutual inductance coupling B and the intrinsic impedances Z_(C) andZ_(S) are related through the total measured impedance Z_(T) across theterminal of the pickup coil 22, as represented by the followingequation:

Z _(T) =Z _(C)(ω² B ² /Z _(S))  (1)

wherein ω is the radian carrier frequency and B is the mutual inductancecoupling B coefficient.

Sensing is performed via monitoring of the changes in the properties ofthe sensing material 14 as probed by the electromagnetic field generatedin the antenna 18 (FIG. 2). Upon reading the RFID sensor 12 with thepickup coil 22, the electromagnetic field generated in the sensorantenna 18 extends out from the plane of the sensor 12 and is affectedby the dielectric property of an ambient environment providing theopportunity for measurements of physical, chemical, and biologicalparameters.

Similarly, sensing is performed via monitoring of the changes in theproperties of the sensing material 14 as probed by the electromagneticfield generated in the complementary sensor 23 (FIG. 3). Upon readingthe RFID sensor 12 with the pickup coil 22, the electromagnetic fieldgenerated in the complementary sensor 23 extends out from the plane ofthe complementary sensor 23 and is affected by the dielectric propertyof an ambient environment providing the opportunity for measurements ofphysical, chemical, and biological parameters.

FIG. 4 illustrates an example of measured responses of an exemplary RFIDsensor 12, in accordance with embodiments of the invention, whichincludes the sensor's full impedance spectra and several individuallymeasured spectral parameters. To selectively detect several vapors orfluids using a single RFID sensor, such as the RFID sensor 12, the realZ_(re)(f) and imaginary Z_(im)(f) parts of the impedance spectraZ(f)=Z_(re)(n+jZ_(im)(f) are measured from the sensor antenna 18 coatedwith a sensing material and at least four spectral parameters arecalculated from the measured Z_(re)(f) and Z_(im)(f), as illustrated inthe plot 30 of FIG. 4. Seven spectral parameters can be calculated asillustrated in the plot 30 of FIG. 4. These parameters include thefrequency position F_(p) and magnitude Z_(p) of Z_(re)(f), the resonantF₁ and anti-resonant F₂ frequencies of Z_(im)(f), the impedancemagnitudes Z₁ and Z₂ at F₁ and F₂ frequencies, respectively, and thezero-reactance frequency F_(Z). Additional parameters, such as qualityfactor may also be calculated. From the measured parameters, resistanceR, capacitance C, and other parameters of the sensing film-coatedresonant antenna 18 can be also determined. Multivariate analysis may beused to reduce the dimensionality of the impedance response, either fromthe measured real Z_(re)(f) and imaginary Z_(im)(f) parts of theimpedance spectra or from the calculated parameters F_(p), Z_(p), F₁ andF₂, and possibly other parameters to a single data point inmulti-dimensional space for selective quantization of different vaporsor fluids, as will be appreciated by those skilled in the art, and aswill be described further below.

The presence of even relatively low levels of interferences (0.1-10 foldoverloading levels) represents a significant limitation for individualsensors due to their insufficient selectivity. This problem can beaddressed with an introduction of a concept of sensor arrays.Unfortunately, in practical situations (e.g. urban, environmental, andworkplace monitoring, breath analysis, and others), sensor arrays sufferfrom interference effects at high (10²-10⁶ fold) overloading levels.These interference effects reduce the use of both sensors and sensorarrays. Advantageously, embodiments described herein provide techniquesto overcome these two key scientific limitations of existing sensors andsensor arrays, such as difficulty or inability of operating with highoverloading from interferences and of selective measurements of multiplevapors and their mixtures using a single sensor.

The well-accepted limitations of impedance spectroscopy in practicalsensors for trace analyte detection include relatively low sensitivityand prohibitively long acquisition times over the broad frequency range.Embodiments described herein enhance the ability to measure changes inproperties of the sensing material by putting the material onto theelectrodes of the resonant LCR sensor circuit. Similarly, the disclosedembodiments enhance the ability to measure changes in properties of thefluid in proximity to the electrodes of the resonant LCR sensor circuit.Experimental testing examined the effects of changing dielectricconstant on sensing electrodes both with and without a resonator.Compared to the conventional impedance spectroscopy, the bare resonantLCR sensor provided an at least 100-fold enhancement in thesignal-to-noise (SNR) over the smallest measured range of Δε with thecorresponding improvement of detection limit of dielectric constantdeterminations.

Performance of the LCR sensor as analyzed using multivariate analysistools provides an advantage of improved selectivity over the processingof individual responses of individual sensors. In particular, testresults indicate the relations between F_(p) and Z_(p) and the relationsbetween calculated sensor resistance R and calculated sensor capacitanceC have much less selectivity between responses to different vapors orfluids as compared to the relations between multivariable parametersthat show more variation, as discussed in detail below. Further, the LCRsensors demonstrate independent contact resistance and contactcapacitance responses that improve the overall selectivity of themultivariable response of the LCR sensors. This selectivity improvementoriginates from the independent contributions of the contact resistanceand contact capacitance responses to the equivalent circuit response ofthe sensor.

Diverse sensing materials may be advantageously utilized on the sensingregion of the LCR resonant sensor because analyte-induced changes in thesensing material film affect the impedance of the antenna LCR circuitthrough the changes in material resistance and capacitance, contactresistance and capacitance between the transducer and sensing material,and resistance and capacitance between the transducer substrate andsensing material. Such changes provide diversity in response of anindividual RFID sensor and provide the opportunity to replace a wholearray of conventional sensors with a single LCR or RFID sensor.

Sensing films for the disclosed LCR and RFID sensors may include avariety of coordination compounds of a primary alkyl amine,trialkylphosphine, trialkylphosphine oxide, alkyldithiocarbamate,alkylxanthate or any combination thereof and a metal nanoparticle, aslong as the environmental changes are detectable by changes in resonantLCR circuit parameters. The primary alkyl amine, trialkylphosphine,trialkylphosphine oxide, alkyldithiocarbamate, alkylxanthate, orcombinations thereof may also be referred to as a ligand or acombination of ligands, which binds to a central metal atom to form acoordination complex. The exemplary coordination compound may berepresented by the formula: (X)_(n)-M where X includes an alkylaminegroup having the formula (R—NH₂), an alkylphosphine having the formula(R₃—P), an alkylphosphine oxide having the formula (R₃P═O), analkyldithiocarbamate having the formula (R₂NCS₂), an alkylxanthatehaving the formula (ROCS₂), or any combination thereof and M is themetal nanoparticle. The value of n may be 1, 2, 3, or greater. The alkylgroup R may be represented by the formula: C_(y)H₂₊₁, where y=1 to 18.Metals that may be used for the metal nanoparticle M include, but arenot limited to, gold, silver, platinum, palladium, alloys thereof, otherhighly conductive metal nanoparticles, or combinations thereof. Incertain embodiments, a weak covalent bond exists between the metalnanoparticle and the ligand. In one embodiment, the coordinationcompound is formed between an octylamine-capped C8 ligand and a goldnanoparticle, as shown in FIG. 5. Other embodiments may utilize othercoordination compounds of a primary alkyl amine, trialkylphosphine,trialkylphosphine oxide, alkyldithiocarbamate, or alkylxanthate, and themetal nanoparticle.

Non-limiting examples of sensing materials include octylamine-capped C8ligand and a gold nanoparticle, octylamine-capped C8 ligand and a silvernanoparticle, octylamine-capped C8 ligand and a platinum nanoparticle,octylamine-capped C8 ligand and a palladium nanoparticle,nonylamine-capped C8 ligand and a gold nanoparticle, andheptylamine-capped C8 ligand and a gold nanoparticle. The use of thesematerials provides the ability to tailor the relative direction ofsensing response upon exposure to vapors of different natures. Thedifferent partition coefficients of vapors into these or other sensingmaterials further modulate the diversity and relative direction of theresponse.

“Composites” are materials made from two or more constituent materialswith significantly different physical or chemical properties, whichremain separate and distinct on a macroscopic level within the finishedstructure. Non-limiting examples of composites include carbon blackcomposites with the various coordination compounds of a primary alkylamine and a metal nanoparticle discussed in detail above.“Nanocomposites” are materials made from two or more constituentmaterials with significantly different physical or chemical properties,which remain separate and distinct on a nanoscale level within thefinished structure. Non-limiting examples of nanocomposites include:carbon nanotube nanocomposites with exemplary coordination compounds;semiconducting nanocrystal quantum dot nanocomposites with exemplarycoordination compounds, metal oxide nanowires, and carbon nanotubes;metal nanoparticles or nanoclusters functionalized with carbonnanotubes.

Sensing materials exhibit analyte responses, which can be described byone or more of three response mechanisms of LCR or RFID sensors, such asresistance changes, dielectric constant changes, and swelling changes. Acomposite sensing material can be constructed which incorporates theexemplary coordination compounds with multiple different individualsensing materials, which each respond to analytes by predominantlydifferent response mechanisms. Such composite sensing materials producean enhanced diversity in the multivariate response. Such compositesensing materials may be homogeneously or inhomogeneously mixed orlocally patterned over specific portions of the LCR resonator.

For example, a wide range of metal oxide semiconductor materials (e.g.ZnO, TiO₂, SrTiO₃, LaFeO₃, etc) exhibit changes in resistance uponexposure to analyte gases, but some mixed metal oxides (e.g. CuO—BaTiO₃,ZnO—WO₃) change their permittivity/capacitance upon exposure to analytevapors. By combining these materials either as mixtures, or by spatiallyseparated deposition onto the same sensor, their separate contributionsto the local environment surrounding the sensor are used to enhance thediversity of response mechanisms for a single analyte, thus enhancingselectivity.

As a further example, the coordination compounds of a primary alkylamine and a metal nanoparticle are used as vapor sensing materialsbecause of their strong changes in resistance due to localized swellinginduced by analyte adsorption into the ligand shell and the subsequentchange in tunneling efficiency between neighboring conductingnanoparticles and dielectric constant changes of the environment betweenthese conducting nanoparticles. In combination with a dielectric polymer(non-limiting examples include silicones, poly(etherurethane),polyisobutylene siloxane fluoroalcohol, etc.), conjugated polymer(polyaniline, polythiophene, poly(vinyl ferrocene),poly(fluorene)-diphenylpropane), poly(3,4-ethylenedioxythiophene)polypyrrole, bilypyrrole) or any other material (non-limiting examplesinclude porphyrins, metalloporphyrins, metallophthalocyanines, carbonnanotubes, semiconducting nanocrystals, metal oxide nanowires) thatresponds to analyte adsorption with more pronounced changes incapacitance or resistance, a sensor with a wider range of analyteresponses is developed. Other examples of materials that may be combinedwith the exemplary coordination compounds are described in U.S. patentapplication Ser. No. 12/942,732 entitled “Highly Selective Chemical andBiological Sensors,” which is incorporated herein by reference.

Further, in order to avoid potentially deleterious effects of disparatematerials on each other in a composite sensing material (e.g. highdielectric constant medium suppressing conduction in a conductive fillermaterial), the material components are chosen to locally phase separatedue to hydrophylic/hydrophobic interactions or mutual immiscibility,allowing the different mechanisms active in each component to be sensedby the sensor. In another embodiment, a composite sensing material canbe formed as sectors of individual materials deposited adjacent to eachother onto a single sensor. In another embodiment, a composite sensingmaterial can be formed as layers of individual materials deposited ontop of each other onto a single sensor.

To further improve selectivity of response, overcoating of sensing filmswith auxiliary membrane filter films may be performed. Non-limitingexamples of these filter films include zeolite, metal-organic framework,and cavitand filters.

These diverse sensing materials shown as non-limiting examples areprovided on the sensing region of the LCR or RFID resonant sensorbecause analyte-induced changes in the sensing material film affect theimpedance of the antenna LCR circuit through the changes in materialresistance and capacitance, contact resistance and capacitance betweenthe transducer and sensing material, resistance and capacitance betweenthe transducer substrate and sensing material. Such changes providediversity in response of an individual RFID sensor and provide theopportunity to replace a whole array of conventional sensors with asingle LCR or RFID sensor, as illustrated further below, with regard toEXPERIMENTAL DATA.

Experimental Data

Resonant antenna structures, such as those described above, were usedfor demonstration of the disclosed techniques. Various sensing materialswere applied onto the resonant antennas by conventional draw-coating,drop coating, and spraying processes. Measurements of the impedance ofthe RFID sensors were performed for example with a network analyzer(Model E5062A, Agilent Technologies, Inc., Santa Clara, Calif.) undercomputer control using LabVIEW. The network analyzer was used to scanthe frequencies over the range of interest (i.e., the resonant frequencyrange of the LCR circuit) and to collect the impedance response from theRFID sensors.

For gas sensing, different concentrations of vapors were generated usingan in-house built computer-controlled vapor-generation system. Collectedimpedance data was analyzed using KaleidaGraph (Synergy Software,Reading, Pa.) and PLS_Toolbox (Eigenvector Research, Inc., Manson,Wash.) operated with Matlab (The Mathworks Inc., Natick, Mass.).

Example. Selective Detection of Individual Nine Alcohols with a SingleSensor

As illustrated in FIGS. 6 and 7, test results were obtained todemonstrate the selective detection of individual, closely relatedvapors, such as alcohols from their homologous series and water vapor asan interferent, using a single sensor, such as the sensor 12 describedabove. As illustrated in FIG. 6, the sensor was exposed to the following10 vapors over a period of time:

1 water 2 methanol 3 ethanol 4 1-propanol 5 1-butanol 6 1-pentanol 71-hexanol 8 1-heptanol 9 1-octanol 10 1-nonanolThe structures of the alcohols 60 are illustrated in FIG. 7.

The sensing material used to coat the RFID tag was carefully chosen andprovided the ability to selectively detect the listed vapors. In thepresent experiment, the chosen sensing material was octylamine-capped C8ligand attached to gold nanoparticles, which was applied as a sensingfilm onto an RFID sensor chip by drop casting. Specifically, thenanoparticles of the sensing material were synthesized as follows. Asolution of HAuCl₄3H₂O (112 mg) was dissolved in 25 mL of water. Whilevigorously stirring the solution, oleylamine (830 mg) dissolved in 25 mLof toluene was added and the mixture was stirred until most or all ofthe Au ions were transferred into the organic layer. After approximately30 minutes, NaBH₄ (0.165 g) in 25 mL of water was added drop-wise andthe reaction mixture was stirred for approximately 2 to 3 hours. Thereaction mixture was phase separated and the toluene layer dried overanhydrous MgSO₄. The toluene layer was reduced to a volume of 5 mL on arotary evaporator. After addition of ethanol (100 mL) to the toluenelayer, the reaction mixture was left at approximately −40 degreesCelsius overnight in a freezer for the nanoparticles to precipitate out.The nanoparticles were separated from the solution by filtering throughfilter paper (Whatman, Piscataway, N.J.) and later redispersed inapproximately 10 mL of toluene.

An interdigital chip served as a complementary sensor that was attachedacross an antenna of a passive RFID tag. The chip was approximately 2 mmby 2 mm and had gold electrodes that were approximately 10 μm wide andspaced approximately 10 μm from each other. During the experiment, theRFID sensor was incrementally exposed to 10 vapors over a period oftime. The test was conducted in steps, where the concentration of eachrespective vapor was increased with each step. Measurements wereperformed with concentrations of all vapors at 0, 0.089, 0.178, 0.267,and 0.356 P/P_(o), where P is the partial pressure and P_(o) is thesaturated vapor pressure. By monitoring changes in certain propertiesand examining various responses over time and at increasingconcentration levels, the data demonstrated the ability to distinguishthe 10 vapors tested in the above-described experiment.

For instance, the frequency position F_(p), the resonant F₁ andanti-resonant F₂ frequencies of Z_(im)(f), the magnitude Z_(p) of thereal part of the total resistance Z_(re)(f), and the impedancemagnitudes Z₁ and Z₂ at F₁ and F₂ frequencies, respectively, areillustrated in FIG. 6, as response plots 40, 42, 48, and 50,respectively. The tests for each vapor were conducted and plotted over 4increments of increasing concentration, as clearly indicated by thestepped nature of the response for each vapor. The relative differencesin the direction and the magnitude of these responses constitute arobust response pattern for these vapors and their differentconcentrations using a single sensor. For example, referring to the plot40 of the frequency position F_(p), the frequency position F_(p) foreach vapor (1-10) exhibits four steps, correlative to the increases inconcentration of each vapor over time. From examining this plot alone,certain of the vapors can clearly be distinguished from one another. Byway of example, the frequency position F_(p) response for 1-heptanol (8)is very strong, and notably discernable from each of the otherresponses. Accordingly, the exemplary RFID sensor is able to selectivelydetect 1-heptanol (8). In contrast, when viewing the frequency positionF_(p) response of 1-pentanol (6), it appears very similar to thefrequency position F_(p) of 1-hexanol (7). Based solely on the frequencyposition F_(p) response, the exemplary RFID sensor may not be suitablefor detecting and distinguishing between these two vapors.

However, as previously described, a number of other responses may alsobe analyzed and may provide further information that may be manipulatedand analyzed in order to provide a way to distinguish vapors, whereinone particular response may not be sufficient. Referring to the testdata for the magnitude Z_(p) response plot 48, the magnitude 4 of1-pentanol (6) is distinguishable from the magnitude 4 of 1-hexanol (7).Accordingly, the exemplary RFID sensor may be sufficient fordistinguishing such vapors, when other responses, such as the magnitudeZ_(p) (as opposed to the frequency position F_(p) response alone), areanalyzed.

One convenient way of analyzing various responses of the sensor is touse principal components analysis (PCA) to produce a multivariatesignature. As will be appreciated, PCA analysis is a mathematicalprocess, known to those skilled in the art, that is used to reducemultidimensional data sets to lower dimensions for analysis. Forinstance, the various responses for each vapor at a given concentrationmay be reduced to a single data point, and from this, a single responsefor each vapor, which may be represented as a vector, may be discerned,as illustrated in FIG. 7. FIG. 7 represents a PCA plot 62 of the variousresponses of the 10 vapors described with reference to FIG. 6. As willbe appreciated, FACTOR1 represents the response with the most variation,while FACTOR2 represents the response with the next most variation. Asshown in FIG. 7, the ten vapors are clearly distinguishable from oneanother. Accordingly, the instant test data provides support for asensor capable of discerning between at least ten vapors, here water(1), methanol (2), ethanol (3), 1-propanol (4), 1-butanol (5),1-pentanol (6), 1-hexanol (7), 1-heptanol (8), 1-octanol (9), and1-nonanol (10). Individual sensors may not achieve this level of vapordiscrimination, while this discrimination was achieved in the Examplewith a single sensor.

In addition, vapor mixtures may also be discernable from the PCA plot.For instance, one may be able to extrapolate a vector plot of a mixtureof methanol (2) and 1-octanol (9). Such additional extrapolated data mayalso be used to selectively detect mixtures of selected vapors. Further,by varying the selected sensing material, even greater numbers ofselective vapor detection has been demonstrated, utilizing a single RFIDsensor.

While only certain features of the invention have been illustrated anddescribed herein, many modifications and changes will occur to thoseskilled in the art. It is, therefore, to be understood that the appendedclaims are intended to cover all such modifications and changes as fallwithin the true spirit of the invention.

1. A method for sensing an analyte of a plurality of analytes,comprising: exposing a sensing material disposed on a single resonantsensor antenna to an environment comprising the plurality of analytes;varying a frequency of the single resonant sensor antenna over afrequency range using a network analyzer; measuring at least sixspectral parameters of the single resonant sensor antenna with thenetwork analyzer; analyzing the at least six spectral parameters overthe frequency range using multivariate analysis to produce amultivariate signature; comparing the multivariate signature topredetermined multivariate signatures formed from test results; anddetecting an analyte of the plurality of analytes based on themultivariate signature and the predetermined multivariate signatures. 2.The method, as set forth in claim 1, wherein the at least six spectralparameters comprise at least six of a frequency of a maximum of a realpart of an impedance spectrum, a magnitude of the real part of theimpedance spectrum, a resonant frequency of an imaginary part of theimpedance spectrum, an anti-resonant frequency of the imaginary part ofthe impedance spectrum, a signal magnitude at the resonant frequency ofthe imaginary of the impedance spectrum, a signal magnitude at theanti-resonant frequency of the imaginary part of the impedance spectrum,and a zero-reactance frequency of the imaginary part of the impedancespectrum.
 3. The method, as set forth in claim 1, wherein measuring atleast six spectral parameters comprises measuring a frequency positionof a real part of an impedance spectrum, and a magnitude of the realpart of the impedance spectrum.
 4. The method, as set forth in claim 1,wherein measuring at least six spectral parameters comprises measuring aresonant frequency of the imaginary part of the impedance spectrum, andan anti-resonant frequency of the imaginary part of the impedancespectrum.
 5. The method, as set forth in claim 1, wherein producing themultivariate signature comprises using principal components analysis. 6.The method, as set forth in claim 1, wherein measuring at least sixspectral parameters of the single resonant sensor antenna with thenetwork analyzer comprises supplying power to an integrated circuit (IC)chip of the resonant sensor at a first predetermined power level.
 7. Amethod for sensing an analyte of a plurality of analytes, comprising:measuring a real part and an imaginary part of an impedance spectrum ofa resonant sensor antenna coated with a coordination compound of aligand and a metal nanoparticle, wherein the ligand comprises a primaryalkyl amine, trialkylphosphine, trialkylphosphine oxide,alkyldithiocarbamate, alkylxanthate or any combination thereof;calculating at least six spectral parameters of the resonant sensorantenna coated with the coordination compound, wherein the at least sixspectral parameters comprise at least six of a frequency of a maximum ofthe real part of the impedance spectrum, a magnitude of the real part ofthe impedance spectrum, a resonant frequency of the imaginary part ofthe impedance spectrum, an anti-resonant frequency of the imaginary partof the impedance spectrum, a signal magnitude at the resonant frequencyof the imaginary part of the impedance spectrum, a signal magnitude atthe anti-resonant frequency of the imaginary part of the impedancespectrum, and a zero-reactance frequency of the imaginary part of theimpedance spectrum; and reducing the impedance spectrum to a single datapoint using multivariate analysis to selectively identify the analyte ofthe plurality of analytes.
 8. The method, as set forth in claim 7,wherein the coordination compound has the formula:(X)_(n)-M, wherein: X comprises an alkylamine group having the formula(R—NH₂), an alkylphosphine having the formula (R₃—P), an alkylphosphineoxide having the formula (R₃P═O), an alkyldithiocarbamate having theformula (R₂NCS₂), an alkylxanthate having the formula (ROCS₂), or anycombination thereof; R comprises an alkyl group, wherein the alkyl grouphas the formula C_(y)H_(2y+1), wherein y=1 to 18; n is 1, 2, or 3; and Mcomprises the metal nanoparticle of gold, silver, platinum, palladium,alloys thereof, highly conductive metal nanoparticles, or anycombination thereof.
 9. The method, as set forth in claim 7, whereinmeasuring the impedance spectrum and calculating the at least sixspectral parameters comprises measuring over a resonant frequency rangeof the resonant sensor.
 10. The method, as set forth in claim 7, whereincalculating at least six spectral parameters comprises calculating thefrequency of the maximum of the real part of the impedance spectrum andthe magnitude of the real part of the impedance spectrum.
 11. Themethod, as set forth in claim 7, wherein calculating at least sixspectral parameters comprises calculating the resonant frequency of theimaginary part of the impedance spectrum and the anti-resonant frequencyof the imaginary part of the impedance spectrum.
 12. The method, as setforth in claim 7, wherein reducing the impedance spectrum to a singledata point comprises calculating a multivariate signature.
 13. Themethod, as set forth in claim 12, wherein calculating the multivariatesignature comprises using principal components analysis.
 14. The method,as set forth in claim 7, wherein measuring the impedance spectrum andcalculating the at least six spectral parameters comprises supplyingpower to an integrated circuit (IC) chip of the resonant sensor at afirst predetermined power level.
 15. The method, as set forth in claim14, wherein measuring the impedance spectrum and calculating at leastsix spectral parameters comprises alternating the power supplied to theIC chip of the resonant sensor between the first predetermined powerlevel and a second predetermined power level.
 16. The method, as setforth in claim 15, wherein the first predetermined power level and thesecond predetermined power level are between −50 dBm and +40 dBm.
 17. Amethod for sensing an analyte of a plurality of analytes, comprising:exposing a radio-frequency identification (RFID) sensor coated with acoordination compound of a ligand and a metal nanoparticle to anenvironment comprising the plurality of analytes, wherein the ligandcomprises a primary alkyl amine, trialkylphosphine, trialkylphosphineoxide, alkyldithiocarbamate, alkylxanthate or any combination thereof;varying a frequency of the RFID sensor over a frequency range using anetwork analyzer; measuring a real part and an imaginary part of animpedance spectrum of the RFID sensor; calculating at least six spectralparameters of the RFID sensor; analyzing the at least six spectralparameters over the frequency range using multivariate analysis toproduce a multivariate signature; and identifying the analyte of theplurality of analytes based on the multivariate signature.
 18. Themethod, as set forth in claim 17, wherein the at least six spectralparameters comprise at least six of a frequency of a maximum of the realpart of the impedance spectrum, a magnitude of the real part of theimpedance spectrum, a resonant frequency of the imaginary part of theimpedance spectrum, an anti-resonant frequency of the imaginary part ofthe impedance spectrum, a signal magnitude at the resonant frequency ofthe imaginary part of the impedance spectrum, a signal magnitude at theanti-resonant frequency of the imaginary part of the impedance spectrum,and a zero-reactance frequency of the imaginary part of the impedancespectrum.
 19. The method, as set forth in claim 17, wherein measuring areal part and an imaginary part of an impedance spectrum of the RFIDsensor comprises supplying power to an integrated circuit (IC) chip ofthe RFID sensor at a first predetermined power level and alternating thepower supplied to the IC chip of the RFID sensor between the firstpredetermined power level and a second predetermined power level. 20.The method, as set forth in claim 17, wherein the frequency range is afrequency range of the RFID sensor.